Potential alternatives to edible oils for biodiesel production - A review of current work

Enhancing heat transfer surface are used in many engineering applications such as heat exchanger, air conditioning, chemical reactor and refrigeration systems, hence many techniques have been investigated on enhancement of heat transfer rate and decrease the size and cost of the involving equipment especially in heat exchangers. One of the most important techniques used are passive heat transfer technique. These techniques when adopted in Heat exchanger proved that the overall thermal performance improved significantly. This paper reviews experimental and numerical works taken by researchers on this technique since 2004 such as twisted tape, wire coil, swirl flow generator,… etc. to enhance the thermal efficiency in heat exchangers and useful to designers implementing passive augmentation techniques in heat exchange. The authors found that variously developed twisted tape inserts are popular researched and used to strengthen the heat transfer efficiency for heat exchangers. The other techniques used for specific work environments are studied in this paper. Twisted tape inserts perform better in laminar flow than turbulent flow. However, the other several passive techniques such as ribs, conical nozzle, and conical ring, etc. are generally more efficient in the turbulent flow than in the laminar flow.

A comprehensive review on passive heat transfer enhancements in pipe exchangers

Economic reasons (material and energy saving) leads to make efforts for making more efficient heat exchange. The heat transfer enhancement techniques are widely used in many applications in the heating process to make possible reduction in weight and size or enhance the performance of heat exchangers. These techniques are classified as active and passive techniques. The active technique required external power while the passive technique does not need any external power. The passive techniques are valuable compared with the active techniques because the swirl inserts manufacturing process is simple and can be easily employed in an existing heat exchanger. Insertion of swirl flow devices enhance the convective heat transfer by making swirl into the bulk flow and disrupting the boundary layer at the tube surface due to repeated changes in the surface geometry. An effort has been made in this paper to carry out an extensive literature review of various turbulators (coiled tubes, extended surfaces (fin, louvered strip, winglet), rough surfaces (Corrugated tube, Rib) and swirl flow devices such as twisted tape, conical ring, snail entry turbulator, vortex rings, coiled wire) for enhancing heat transfer in heat exchangers. It can be concluded that wire coil gives better overall performance if the pressure drop penalty is considered. The use of coiled square wire turbulators leads to a considerable increase in heat transfer and friction loss over those of a smooth wall tube.

Review of heat transfer enhancement methods: Focus on passive methods using swirl flow devices

Energy is fundamental to the quality of life in the earth. Meeting the growing demand for energy sustainably is one of the major challenges of the 21st century. Indonesia is a developing country and the world's fourth most populous nation. Total annual energy consumption increased from 300,147 GWh in 1980, 625,500 GWh in 1990, 1,123,928 in 2000 and to 1,490,892 in 2009 at an average annual increase of 2.9%. Presently, fossil-fuel-based energies are the major sources of energy in Indonesia. During the last 12 years, Indonesia has recorded the most severe reduction in fossil fuel supplies in the entire Asia-Pacific region. This reduction has stimulated promoting the usage of renewable energy resources capable of simultaneously balancing economic and social development with environmental protection. Biodiesel is an alternative and environmentally friendly fuel that will participate in increasing renewable energy supply. Jatropha curcas is one of biodiesel resources that offer immediate and sustained greenhouse gas advantages over other biodiesel resources. Globally, J. curcas has created an interest for researchers because it is non-edible oil, does not create a food versus fuel conflict and can be used to produce biodiesel with same or better performance results when testing in diesel engines. The present study is concerned with the prospect of biodiesel produced from J. curcas in Indonesia. The first part gives a summary and overview of energy resources and consumption in the country, second part discusses the potential of biodiesel as a powerful renewable energy resource and third part investigates the potential of J. curcas as a feedstock for biodiesel in Indonesia. The final part discusses the development of biodiesel market in Indonesia. The paper found out that the production of biodiesel from J. curcas offers many social, economical and environmental benefits for the country and can play a great role to solve the problem of energy crisis in Indonesia.

A review on prospect of Jatropha curcas for biodiesel in Indonesia

In this contribution, authors present a review on the state-of-the-art in the utilization of industrial and agricultural waste materials for the development of metal–matrix composites (MMCs), providing, through the judicious analysis of an ample and varied references source – from the oldest to the newest ones – an insight into the challenges and opportunities for the exploitation to their full potential. In addition to its topicality, the novelty of this contribution lies in the presentation of key statistical, technical, and property-related information of a comprehensive variety of waste materials classed into two main groups, namely, fly ash reinforced MMCs and MMCs derived from other waste materials. Although fly ash has been exploited in a broad range of applications, the attention paid for its use in the development of MMCs seems to be insufficient. A purposely designed chart helped to pinpoint the more demanding and profitable applications of fly ash, and establish strategic opportunity ar...

Development of metal-matrix composites from industrial/agricultural waste materials and their derivatives

The present study investigates the use of artificial neural network modelling for prediction of emission parameters of a four stroke single cylinder variable compression ratio diesel engine. ANN model was developed to predict emissions namely CO, NOX and HC. Emission data was collected by conducting experiments by varying compression ratio, Injection time, and injection pressure in four steps and load in five steps. Two training algorithms traingd and trainlm with hidden nodes varying from 3 to 20 in step of one were developed and trained. Best network from 36 networks was selected based on MSE, regression coefficients for training, validation, testing and correlation coefficient for prediction of unseen data. The best model was found to be Levenberg–Marquardt algorithm with 17 neurons and regression coefficients for training, validation and testing are 0.99628, 0.99561, 0.99472 and 0.99577 respectively. The correlation coefficient R for training data is 0.99643 and for unseen data is 0.99322. The regression coefficients for prediction of training sets of CO, NOX and HC are 0.99643, 0.99486 and 0.99601 respectively. The average % error for prediction of CO, NOX and HC are -0.16178, -0.38814 and 0.7459 respectively which are less than 1. It is found that artificial neural networks serve as an excellent tool for prediction of emissions from diesel engine under variable operating and design parameters.

Neural Network—Based Diesel Engine Emissions Prediction for Variable Injection Timing, Injection Pressure, Compression Ratio and Load Conditions

Design and operating parameters of diesel engine were optimized in the present work with respect to performance, combustion and emission parameters. The goal is to reduce brake specific fuel consumption (BSFC), exhaust gas temperature (EGT), ignition delay (ID), emissions (CO, NOx, HC) and to increase peak pressure (PP), brake thermal efficiency (BTHE), heat release (HR) simultaneously with least number of experimental runs. The objective was accomplished through experimental investigations, design of experiments, Taguchi method and Grey Relational Analysis. Four parameters viz. injection timing (IJT), injection pressure (IP), compression ratio (CR) and load were varied at four levels and the (nine) responses were recorded. Taguchi approach was applied to individual response and observed that optimal factor settings for various responses are different.

/pdf/optimization-of-diesel-engine-parameters-for-performance-1iu90ssjfn.pdf

Optimization of Diesel Engine Parameters for Performance, Combustion and Emission Parameters using Taguchi and Grey Relational Analysis

The main objective of this paper is pioneering an innovative tactic for the synchronization of multi-stage, multi-line, production system. This tactic is mainly depends on the optimization policy, by means of distinct event simulation process for modeling, analysis and distinction of the execution of two alternatives of Kanban control mechanism namely SEKCS (Simultaneous Extended Kanban Control System) and IEKCS (Independent Extended Kanban Control System). At this juncture the authors putting forward the two variants of Extended Kanban control system with the hybridization of CONWIP control policy to incite HSEKCS (Hybrid Simultaneous Extended Kanban Control System) and HIEKCS (Hybrid Independent Extended Kanban Control System) to make use of pooled benefits of a representative production situation in addition to improve the outcome. Therefore in this study the comparison in between different systems of proposed HEKCS specifically are HSEKCS and HIEKCS compared with the Extended Kanban Control Systems variants SEKCS and IEKCS. Simulation studies were conducted for all the five control policies considered and modeled on a multi-line, multi-stage assembly production control system. The relative performance parameters like Throughput or Production rate, Average Waiting Time and Average Work-in-Process, were assessed by means of exponentially varying demands.

Evaluation of Manufacturing Process Performance by CONWIP Hybridization of Pull Controlled Production Systems

Combined cycle power plants play an important role in the present energy sector. The main challenge in designing a combined cycle power plant is how to transfer gas turbine exhaust heat to the steam cycle to achieve optimum steam turbine output. Most of the combined cycle developers focus on the gas turbine and steam turbine, but the performance of the heat recovery steam generator (HRSG) strongly affects the overall performance of the combined cycle power plant. Therefore, the present article undertakes the problem of optimal utilization of the waste heat from gas turbine exhaust with dual pressure HRSG configuration. The combined cycle efficiency has been analyzed parametrically from both the first and second law of thermodynamics. It is observed that in the dual cycle the high-pressure steam pressure must be relatively high, and low-pressure steam pressure must be low for better heat recovery from HRSG.

Performance Simulation of Dual Pressure HRSG in Combined Cycle Power Plant

Effective utilization of fuel in diesel engines is the major challenge posed to the engine designers today, due to large demand of fuel. In this context, control of design, as well as operating parameters for better performance are focused in the present work. Experiments are done on a 4-s, variable compression ratio (VCR) diesel engine and the required data is collected by varying fuel injection timing (IJT), compression ratio (CR), load and fuel injection pressure (IP). The combustion parameters, viz. combustion duration (CD), ignition delay (ID), peak pressure (PP) and heat release (HR) are determined at various operating conditions, as these parameters could influence fuel consumption and performance. For the investigation purpose, an artificial neural network (ANN) with back propagation algorithm is adopted. ANN is trained with the experimental data. The number of nodes in the hidden layer is varied from 3 to 22, to architect a suitable network for the prediction of combustion parameters with good accuracy. Test results show that network with 4-19-4 architecture with trainlm algorithm can predict the four parameters (ID, CD, PP and HR) with correlation coefficients as 0.9892, 09892, 0.9944 and 0.9909 taken in the order.

A. V. Sita Rama Raju

Papers

Neural Network—Based Diesel Engine Emissions Prediction for Variable Injection Timing, Injection Pressure, Compression Ratio and Load Conditions

Optimization of Diesel Engine Parameters for Performance, Combustion and Emission Parameters using Taguchi and Grey Relational Analysis

Evaluation of Manufacturing Process Performance by CONWIP Hybridization of Pull Controlled Production Systems

Performance Simulation of Dual Pressure HRSG in Combined Cycle Power Plant

Development of Back Propagation Neural Network (BPNN) Model to Predict Combustion Parameters of Diesel Engine